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If you thought storing data inside DNA was cool, here’s something even more fascinating. Scientists at the University of Texas at Austin (UT Austin) have invented a way to store digital information inside synthetic polymer molecules. In short, they are transforming tiny bits of plastic into memory banks.

They even used their molecular system to encode a complex 11-character password and then decode it using only electrical signals, without any power, and the expensive and bulky tools typically used for reading molecular data.

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Ischaemic heart disease remains the main cause of death worldwide. 1 Within its multifactorial aetiology low-density lipoprotein (LDL) and other apolipoprotein (apo) B-containing lipoproteins play a central, causal role, promoting the development of the underlying process of atherosclerosis. The use of statins and other drugs—ezetimibe, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, bempedoic acid—to lower LDL is a central strategy in the prevention of atherosclerotic cardiovascular disease (ASCVD) in both primary and secondary settings. 2 However, in many individuals, a substantial ASCVD risk remains after LDL-cholesterol (LDL-C) goal achievement, and elevated plasma triglyceride (TG) is recognised as an important component of this residual risk. 3 Plasma TG, or more specifically TG-rich lipoproteins (TRL), is therefore an additional target for lipid-lowering therapy. Outcome studies of TG lowering using classical drugs such as fibrates and high-dose niacin when added to statins failed to demonstrate further ASCVD risk reduction, although retrospective analyses suggest that subgroups characterised by high TG and low high-density lipoprotein (HDL) may have positive results. 4–7 An alternative approach, treatment with high-dose eicosapentaenoic acid (EPA), has been shown to reduce cardiovascular risk in patients with (and without) hypertriglyceridaemia who are on statins. 8–10

This review explores the concepts behind, and practical implementation of, an evidence-based therapeutic strategy that tailors further intervention according to the plasma lipid profile in patients on standard statin therapy who are often undertreated. 11

Genetic analyses provide robust evidence that elevated TG is a causal risk factor for ASCVD 12 13 and underpin the finding from epidemiological studies that raised TG levels are positively and linearly related to cardiovascular risk (figure 1A). 14 15 The importance of these observations is that they reveal an often unaddressed major risk factor that is of particular relevance in people with obesity or type 2 diabetes in whom TG levels are frequently elevated. 16 Further, outcome trials have shown that elevated TG levels (again especially in type 2 diabetics) are associated with high residual cardiovascular risk in statin-treated patients with established cardiovascular disease, even if they have well-controlled LDL-C. 17–19.

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Depression, characterized by persistent sadness, hopelessness and a lack of interest in previously enjoyed activities, is one of the most common mental health disorders. Recent estimates by the World Health Organization (WHO) suggest that approximately 5% of the global population suffers from depression.

For decades, researchers have been trying to devise safe and effective treatments for that cause minimal or no side effects. This led to the introduction of a wide range of strategies, ranging from psychotherapy and to a wide range of pharmacological drugs, including (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), monoamine oxidase inhibitors (MAOIs) and atypical antidepressants.

Most people diagnosed with depression eventually find a suitable treatment for them via a trial-and-error process, ultimately leading to their recovery. Some individuals, however, can experience for prolonged periods of time, finding that no treatment ultimately eases their symptoms.

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Artificial photosynthesis is a technology with immense potential that aims to emulate the natural photosynthetic process. The process of natural photosynthesis involves the conversion of solar energy into chemical energy, which is stored in organic compounds. Catalysis is an essential aspect of artificial photosynthesis, as it facilitates the reactions that convert solar energy into chemical energy. In this review, we aim to provide an extensive overview of recent developments in the field of artificial photosynthesis by catalysis. We will discuss the various catalyst types used in artificial photosynthesis, including homogeneous catalysts, heterogeneous catalysts, and biocatalysts.

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Proton beams with giga-electron-volt (GeV) energies—once thought to be achievable only with massive particle accelerators—may soon be generated in compact setups thanks to a breakthrough by researchers at The University of Osaka.

A team led by Professor Masakatsu Murakami has developed a novel concept called micronozzle acceleration (MNA). By designing a microtarget with tiny nozzle-like features and irradiating it with ultraintense, ultrashort laser pulses, the team successfully demonstrated—through advanced numerical simulations—the generation of high-quality, GeV-class proton beams: a world-first achievement.

The article, “Generation of giga-electron-volt proton beams by micronozzle acceleration,” was published in Scientific Reports.

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A research team has developed autonomous driving software that allows inexpensive sensors to detect transparent obstacles such as glass walls, providing an alternative to high-performance sensors. This technology can be used in existing robots, negating the need for additional equipment while ensuring detection performance that is equal to that offered by expensive conventional equipment.

The paper is published in the journal IEEE Transactions on Instrumentation and Measurement. The team was led by Professor Kyungjoon Park at the Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science & Technology.

Autonomous driving robots typically use LiDAR sensors to detect their surroundings and navigate. Functioning as “laser eyes,” expensive LiDAR sensors determine distance and structure by projecting light and measuring reflection time.

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Our forward-leaning, innovative spirit is backed by a legacy of expertise that began at the dawn of the space age.

Our mission experience in space runs deep, we know our customers well, and our capabilities are unmatched. This is what allows us to provide reliable, agile and affordable space solutions to best serve our customers.

From defending freedom to advancing human discovery, we are defining what is possible in space every day.

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A new AI-powered method is changing how scientists measure the universe. Developed by researchers at the Flatiron Institute and their partners, this technique offers a far more accurate way to determine the cosmos’ key properties.

The approach, known as Simulation-Based Inference of Galaxies (SimBIG), pulls hidden clues from galaxy patterns. It goes beyond older techniques by uncovering information that was previously out of reach.

Using AI, the team cut uncertainty in critical parameters—like how clumpy matter is in the universe—to less than half. These results match closely with other cosmic measurements, including the light from the universe’s earliest moments.

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